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Service architecture for entity and relationship detection in unstructured text
Techniques for entity and relationship detect from unstructured text as a service are described. A service may receive a request to …
Thiruvarul Selvan Senthivel
,
Varun Sembium Varadarajan
,
Borui Zhang
,
Tiberiu Mircea Doman
,
Parminder Bhatia- Arun Kumar Ravi
,
Mohammed Khalilia
,
Emine Busra Celikkaya
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Google Patents
Wojood - Arabic NER
Wojood consists of about 550K tokens (MSA and dialect) that are manually annotated with 21 entity types (e.g., person, organization, location, event, date, etc). It covers multiple domains and was annotated with nested entities. The corpus contains about 75K entities and 22.5% of which are nested. A nested named entity recognition (NER) model based on BERT was trained (F1-score 88.4%).
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Comprehend Medical
Amazon Comprehend Medical is a HIPAA-eligible natural language processing (NLP) service that uses machine learning that has been pre-trained to understand and extract health data from medical text, such as prescriptions, procedures, or diagnoses.
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